Poll watch

Connecting to the postgres sql database

library(odbc)
library(DBI)
library(RPostgreSQL)

password = "Kingjames1611"
DBI::dbDriver('PostgreSQL')

<PostgreSQLDriver>

drv=dbDriver("PostgreSQL")
con=dbConnect(drv,dbname="practical_sql",
              host="localhost",
              port=5432,
              user="postgres",
              password=password)

dbListTables(conn = con)

[1] "spatial_ref_sys" "poll_watch"     

using the database

library(odbc)
library(DBI)
library(RPostgreSQL)

## Actual code for automating the database

query = "(

select  
        question_id,
        poll_id,
        cycle,
        state,
        pollster_id::float::numeric,
        pollster,
        sponsors,
        display_name,
        pollster_rating_id,
        pollster_rating_name,
        fte_grade,
        sample_size::float8::numeric::double precision--when applicable,
        population,
        population_full,methodology,
        office_type,
        start_date::date,
        end_date::date,
        election_date::date,
        internal,
        partisan,
        tracking,
        nationwide_batch,
        ranked_choice_reallocated,
        created_at::timestamptz::timestamp::timestamptz,
        notes,
        url as source,
        race_id,
        answer,
        candidate_party,
        pct::float8::numeric::double precision--when applicable



from poll_watch
where candidate_party = 'REP'
or candidate_party = 'DEM'
and created_at > '2020-09-15'

order by end_date desc,
         start_date,
         methodology








)"


#processing the query

result_db<- RPostgreSQL::dbGetQuery(conn = con,statement = query)
result_db

Keep in mind that you can also plot the information contained in the database right here in R.

summary(result_db)

  question_id        poll_id     
 Min.   : 92078   Min.   :57025  
 1st Qu.:112656   1st Qu.:62539  
 Median :122108   Median :65817  
 Mean   :118354   Mean   :65005  
 3rd Qu.:128123   3rd Qu.:68436  
 Max.   :130600   Max.   :70106  
                                 
    cycle              state          
 Length:4229        Length:4229       
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      
  pollster_id     pollster        
 Min.   :  11   Length:4229       
 1st Qu.: 568   Class :character  
 Median :1189   Mode  :character  
 Mean   :1004                     
 3rd Qu.:1416                     
 Max.   :1624                     
                                  
   sponsors         display_name      
 Length:4229        Length:4229       
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      
 pollster_rating_id pollster_rating_name
 Min.   :  3.0      Length:4229         
 1st Qu.:144.0      Class :character    
 Median :245.0      Mode  :character    
 Mean   :271.1                          
 3rd Qu.:383.0                          
 Max.   :619.0                          
 NA's   :1                              
  fte_grade           population    
 Length:4229        Min.   :   140  
 Class :character   1st Qu.:   760  
 Mode  :character   Median :  1000  
                    Mean   :  2238  
                    3rd Qu.:  1441  
                    Max.   :145588  
                                    
 population_full    methodology       
 Length:4229        Length:4229       
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      
 office_type          start_date        
 Length:4229        Min.   :2018-11-12  
 Class :character   1st Qu.:2019-10-19  
 Mode  :character   Median :2020-04-12  
                    Mean   :2020-03-06  
                    3rd Qu.:2020-08-16  
                    Max.   :2020-09-29  
                                        
    end_date          election_date       
 Min.   :2018-11-13   Min.   :2020-11-03  
 1st Qu.:2019-10-26   1st Qu.:2020-11-03  
 Median :2020-04-15   Median :2020-11-03  
 Mean   :2020-03-11   Mean   :2020-11-03  
 3rd Qu.:2020-08-25   3rd Qu.:2020-11-03  
 Max.   :2020-09-30   Max.   :2020-11-03  
                                          
  internal         partisan        
 Mode :logical   Length:4229       
 FALSE:4219      Class :character  
 TRUE :10        Mode  :character  
                                   
                                   
                                   
                                   
 tracking       nationwide_batch
 Mode:logical   Mode :logical   
 TRUE:663       FALSE:4229      
 NA's:3566                      
                                
                                
                                
                                
 ranked_choice_reallocated
 Mode :logical            
 FALSE:4229               
                          
                          
                          
                          
                          
   created_at                     notes          
 Min.   :2018-12-06 14:40:00   Length:4229       
 1st Qu.:2019-11-04 08:40:00   Class :character  
 Median :2020-04-25 01:02:00   Mode  :character  
 Mean   :2020-03-22 08:35:41                     
 3rd Qu.:2020-09-02 20:32:00                     
 Max.   :2020-10-01 13:02:00                     
                                                 
    source             race_id    
 Length:4229        Min.   :6210  
 Class :character   1st Qu.:6210  
 Mode  :character   Median :6215  
                    Mean   :6250  
                    3rd Qu.:6241  
                    Max.   :8718  
                                  
    answer          candidate_party   
 Length:4229        Length:4229       
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      
                                      
      pct       
 Min.   :21.00  
 1st Qu.:41.00  
 Median :44.00  
 Mean   :43.73  
 3rd Qu.:47.00  
 Max.   :67.00  
                

library(ggplot2)
library(esquisse)
library(gganimate)


#esquisser(result_db
library(dplyr)
library(ggplot2)

p<-result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = "", y = pct, fill = candidate_party) +
 geom_boxplot() +
 scale_fill_hue() +
 theme_classic()+labs(x = "candidate's party", y = "percentage", title = "Boxplot track of 2020 presidential election", caption = "Prepared by Joel Rodriguez")+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

p+transition_time(start_date) +
  ease_aes() #+
  #transition_time(candidate_party) +
 # ease_aes('linear')

library(esquisse)
library(gganimate)
library(dplyr)
library(ggplot2)

p<-result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = "", y = pct, fill = candidate_party) +
 geom_boxplot() +
 scale_fill_hue() +
 theme_classic()+labs(x = "candidate's party", y = "percentage", title = "Boxplot track of 2020 presidential election", caption = "Prepared by Joel Rodriguez")
 p+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

NA
NA

library(dplyr)
library(ggplot2)
library(plotly)

Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Attaching package: 㤼㸱plotly㤼㸲

The following object is masked from 㤼㸱package:ggplot2㤼㸲:

    last_plot

The following object is masked from 㤼㸱package:stats㤼㸲:

    filter

The following object is masked from 㤼㸱package:graphics㤼㸲:

    layout

mult<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = answer, y = pct, fill = candidate_party) +
 geom_boxplot() +
 scale_fill_hue() +
 theme_minimal() +
 facet_wrap(vars(state))+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))
ggplotly(mult)

`group_by_()` is deprecated as of dplyr 0.7.0.
Please use `group_by()` instead.
See vignette('programming') for more help
This warning is displayed once every 8 hours.
Call `lifecycle::last_warnings()` to see where this warning was generated.

library(ggplot2)
library(esquisse)
library(plotly)

AA<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_density(adjust = 1L) +
 scale_fill_hue() +
 labs(x = "Percentage", y = "Density", title = "Density Plot presidential election 2020",caption = "Prepared by Joel Rodriguez") +
 theme_minimal()


ggplotly(AA)

library(gganimate)
result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = "", y = pct, fill = candidate_party) +
 geom_violin(adjust = 1L, scale = "area") +
 scale_fill_hue() +
 labs(x = "Percentage", y = "Density", title = "Density Plot presidential election 2020",caption = "Prepared by Joel Rodriguez") +
 theme_minimal()+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))+transition_time(start_date) +
  ease_aes()+transition_time(start_date) +
  ease_aes() 

library(gganimate)
library(plotly)
A<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = "", y = pct, fill = candidate_party) +
 geom_violin(adjust = 1L, scale = "area") +
 scale_fill_hue() +
 labs(x = "Percentage", y = "Density", title = "Density Plot presidential election 2020",caption = "Prepared by Joel Rodriguez") +
 theme_minimal()

ggplotly(A)

NA

result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_histogram(bins = 28L) +
 scale_fill_brewer(palette = "Set1") +
 labs(x = "Percentage", y = "Density", title = "Density Plot presidential election 2020",caption = "Prepared by Joel Rodriguez") +
 theme_minimal() +
 theme(legend.position = "none")+transition_time(start_date) +
  ease_aes()

g4<- result_db %>%
 filter(created_at >= 
          "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct,
     fill = candidate_party,fill= candidate_party) +
 geom_histogram(bins = 28L) +
 scale_fill_brewer(palette = "Set1") +
 labs(x = "Percentage",
      y = "Density", 
      title = "Density Plot presidential election 2020",caption = "Prepared by Joel Rodriguez") +
 theme_minimal() +
 theme(legend.position = "none")+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

Duplicated aesthetics after name standardisation: fill

ggplotly(g4)

library(dplyr)
library(ggplot2)
library(plotly)

pk<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = answer) +
 geom_density(adjust = 0.2) +
 scale_fill_hue() +
 theme_minimal()+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))+ labs(x = "percentage", title = "Plots divided by candidate",caption = "Prepared by Joel Rodriguez")

ggplotly(pk)

library(dplyr)
library(ggplot2)

result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = answer) +
 geom_density(adjust = 0.2) +
 scale_fill_hue() + labs(x = "percentage", title = "Plots divided by candidate",caption = "Prepared by Joel Rodriguez")

 theme_minimal()

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  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ plot.title                :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 1.2
  ..$ hjust        : num 0
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 5.5points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.title.position       : chr "panel"
 $ plot.subtitle             :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : NULL
  ..$ hjust        : num 0
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 0points 0points 5.5points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.caption              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 0.8
  ..$ hjust        : num 1
  ..$ vjust        : num 1
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 5.5points 0points 0points 0points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.caption.position     : chr "panel"
 $ plot.tag                  :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
  ..$ size         : 'rel' num 1.2
  ..$ hjust        : num 0.5
  ..$ vjust        : num 0.5
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ plot.tag.position         : chr "topleft"
 $ plot.margin               : 'margin' num [1:4] 5.5points 5.5points 5.5points 5.5points
  ..- attr(*, "unit")= int 8
 $ strip.background          : list()
  ..- attr(*, "class")= chr [1:2] "element_blank" "element"
 $ strip.background.x        : NULL
 $ strip.background.y        : NULL
 $ strip.placement           : chr "inside"
 $ strip.text                :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : chr "grey10"
  ..$ size         : 'rel' num 0.8
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : NULL
  ..$ lineheight   : NULL
  ..$ margin       : 'margin' num [1:4] 4.4points 4.4points 4.4points 4.4points
  .. ..- attr(*, "unit")= int 8
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ strip.text.x              : NULL
 $ strip.text.y              :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
  ..$ colour       : NULL
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  ..$ vjust        : NULL
  ..$ angle        : num -90
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 $ strip.switch.pad.grid     : 'simpleUnit' num 2.75points
  ..- attr(*, "unit")= int 8
 $ strip.switch.pad.wrap     : 'simpleUnit' num 2.75points
  ..- attr(*, "unit")= int 8
 $ strip.text.y.left         :List of 11
  ..$ family       : NULL
  ..$ face         : NULL
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  ..$ size         : NULL
  ..$ hjust        : NULL
  ..$ vjust        : NULL
  ..$ angle        : num 90
  ..$ lineheight   : NULL
  ..$ margin       : NULL
  ..$ debug        : NULL
  ..$ inherit.blank: logi TRUE
  ..- attr(*, "class")= chr [1:2] "element_text" "element"
 - attr(*, "class")= chr [1:2] "theme" "gg"
 - attr(*, "complete")= logi TRUE
 - attr(*, "validate")= logi TRUE

pk<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = answer) +
 geom_density(adjust = 6L) +
 scale_fill_hue() +
 theme_minimal() +
 facet_wrap(vars(population_full))+ labs(x = "percentage", title = "Plots divided by methodology",caption = "Prepared by Joel Rodriguez")+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

ggplotly(pk)

Groups with fewer than two data points have been dropped.Groups with fewer than two data points have been dropped.

library(forecast)

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

library(dplyr)
#library(highcharter)
library(tidyselect)
library(esquisse)


a = result_db$pct
a%>%forecast%>%plot()

NA
NA

library(dplyr)
library(ggplot2)
library(dplyr)
library(ggplot2)

result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_density(adjust = 1L) +
 scale_fill_viridis_d(option = "plasma") +
 theme_minimal()+ labs(x = "percentage", title = "Plots divided by methodology",caption = "Prepared by Joel Rodriguez")+transition_time(start_date) +
  ease_aes())

Error: unexpected ')' in:
" theme_minimal()+ labs(x = "percentage", title = "Plots divided by methodology",caption = "Prepared by Joel Rodriguez")+transition_time(start_date) +
  ease_aes())"

library(dplyr)
library(ggplot2)
library(dplyr)
library(ggplot2)
library(plotly)

g3<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_density(adjust = 1L) +
 scale_fill_viridis_d(option = "plasma") +
 theme_minimal()+ labs(x = "percentage", title = "Plots divided by methodology",caption = "Prepared by Joel Rodriguez") + theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

ggplotly(g3)

NA
NA

library(dplyr)
library(ggplot2)
result_db %>%
 filter(created_at >=
          "2020-09-18 09:12:00" &
          created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_histogram(bins = 30L) +
 scale_fill_viridis_d(option = "cividis") +
 labs(x = "percentage", title = "Plots divided by methodology") +
 theme_minimal() +
 facet_wrap(vars(notes))+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

library(dplyr)
library(ggplot2)
result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_density(adjust = 1L) +
 scale_fill_viridis_d(option = "cividis") +
 labs(x = "percentage", title = "Plots divided by methodology") +
 theme_minimal() +
 facet_wrap(vars(notes))+  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))

library(dplyr)
library(ggplot2)
library(plotly)
g1<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = candidate_party) +
 geom_density(adjust = 1L) +
 scale_fill_viridis_d(option = "cividis") +
 labs(x = "percentage", title = "Plots divided by methodology") +
 theme_minimal() +
 facet_wrap(vars(tracking)) + theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))
ggplotly(g1)

library(dplyr)
library(ggplot2)
library(dplyr)
library(ggplot2)

result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = pct, fill = display_name, colour = partisan) +
 geom_histogram(bins = 29L) +
 scale_fill_viridis_d(option = "viridis") +
 scale_color_viridis_d(option = "viridis") +
 theme_minimal()

result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = answer, y = pct, colour = candidate_party) +
 geom_boxplot(fill = "#238b45") +
 scale_color_viridis_d(option = "cividis") +
 labs(x = "Candidates",y='percentage', title = "Plots divided by methodology",caption = "Prepared by Joel Rodriguez") +
 theme_bw() +
 facet_wrap(vars(candidate_party), scales = "free_x")+transition_time(start_date) +
  ease_aes() + theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )

library(plotly)
gg<- result_db %>%
 filter(created_at >= "2020-09-18 09:12:00" & created_at <= "2020-10-01 17:02:00") %>%
 ggplot() +
 aes(x = answer, y = pct, colour = candidate_party) +
 geom_boxplot(fill = "#238b45") +
 scale_color_viridis_d(option = "cividis") +
 labs(y= "percentage",x= 'candidates' , "Plots divided by methodology",caption = "Prepared by Joel Rodriguez") +
 theme_bw() +
 facet_wrap(vars(candidate_party), scales = "free_x") +
  
  theme(
  panel.background = element_rect(fill = "lightblue",
                                colour = "lightblue",
                                size = 0.5, linetype = "solid"),
  panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "white"), 
  panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
                                colour = "white")
  )+theme(plot.background = element_rect(fill = "lightblue"))


ggplotly(gg)

library(odbc)
library(DBI)
library(RPostgreSQL)

#dbDisconnect(con)